This invention relates generally to aircraft engine power management schemes and more particularly, to methods and apparatus for nonlinear model predictive control of an aircraft gas turbine.
Gas turbines are used in different environments, such as, for example, but not limited to, providing propulsion as aircraft engines and for power generation in both land based power systems and sea borne power systems. The gas turbine model considered is a low bypass, two rotor, turbojet with a variable exhaust area that would be used in military aircraft applications. During normal operation this turbine experiences large changes in ambient temperature, pressure, Mach number, and power output level. For each of these variations the engine dynamics change in a significant nonlinear manner. Careful attention is typically paid by the controller during engine operation to ensure that the mechanical, aerodynamic, thermal, and flow limitations of the turbo machinery is maintained. In addition, the control authority is restricted by the actuator rate and saturation limits. Current technology solves this nonlinear constrained problem using many SISO linear controllers in concert that are gain scheduled and min/max selected to protect against engine limits. While the existing methods have many merits, there exists a need to solve the problem using nonlinear model predictive control (NMPC), which handles the nonlinearities and constraints explicitly and in a single control formulation.
In one aspect, a method of designing the operations and controls of an aircraft gas turbine engine is provided. The method includes generating an operations model for the gas turbine, generating at least one objective function, defining operations and control constraints for the operations model of the gas turbine, and providing an online dynamic optimizer/controller that dynamically optimizes and controls operation of the gas turbine using model predictive control based on the operations model and the operations and control constraints using an Extended Kalman Filter for estimation.
In another aspect, a system for designing the operations and controls of an aircraft gas turbine engine is provided. The system includes a computing unit with an input unit for generating an operations model for the aircraft gas turbine engine, generating at least one objective function and for defining operations and controls constraints for the operations model of the aircraft gas turbine engine, and a dynamic online optimizer/controller configured to dynamically optimize and control operation of the gas turbine using model predictive control based on the operations model and the operations and control constraints using an Extended Kalman Filter for estimation.
In yet another aspect, a non-linear model-based control method for controlling propulsion in a aircraft gas turbine engine is provided. The method includes a) obtaining information about the current state of the engine using an Extended Kalman Filter, b) updating model data information about the engine in an model-based control system to reflect the current state of the engine, c) determining the optimal corrective action to take given the current state of the engine, the objective function, and the constraints of the engine, d) outputting a control command to implement the optimal corrective action, and e) repeating steps a)-d) as necessary to ensure the performance of the engine is optimized at all times.